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Design and Build A Customer-Finding Application For Leko Restaurant Using The K-Means Algorithm Mohamad Yusuf; Muhaimin Hasanudin; Ifan Prihandi
IJISTECH (International Journal of Information System and Technology) Vol 6, No 2 (2022): August
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Warung Makan Leko is one of the restaurants in the Jakarta area that offers local cuisine, a diverse menu and delivery orders via phone order. Customers are one source of income for Warung Makan Leko. The amount of competition makes Warung Makan Leko have difficulty in retaining loyal customers. For this reason, further analysis is needed to find out who these potential customers are. Then an application was developed to classify customer data using the K-Means (clustering) algorithm. The data used as an example in this study is the sales transaction data of Warung Makan Leko. Run the process to calculate the total sales to customers and the number of transactions with customers to classify customer data. The K-Means clustering method tries to group the existing data into groups. Data in groups have the same properties. Customer data is grouped into two clusters, no and implicit. Each cluster is then classified based on the prioritized criteria. The cluster with the highest centroid value is the cluster that is rewarded, and the cluster with the lowest centroid value is the non-rewarded cluster. The results of this process form clusters, which are used for advice and consideration to determine sales strategy, namely to reward customers who rank higher in the cluster

Design and Build A Customer-Finding Application For Leko Restaurant Using The K-Means Algorithm Mohamad Yusuf; Muhaimin Hasanudin; Ifan Prihandi
IJISTECH (International Journal of Information System and Technology) Vol 6, No 2 (2022): August
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i2.238

Warung Makan Leko is one of the restaurants in the Jakarta area that offers local cuisine, a diverse menu and delivery orders via phone order. Customers are one source of income for Warung Makan Leko. The amount of competition makes Warung Makan Leko have difficulty in retaining loyal customers. For this reason, further analysis is needed to find out who these potential customers are. Then an application was developed to classify customer data using the K-Means (clustering) algorithm. The data used as an example in this study is the sales transaction data of Warung Makan Leko. Run the process to calculate the total sales to customers and the number of transactions with customers to classify customer data. The K-Means clustering method tries to group the existing data into groups. Data in groups have the same properties. Customer data is grouped into two clusters, no and implicit. Each cluster is then classified based on the prioritized criteria. The cluster with the highest centroid value is the cluster that is rewarded, and the cluster with the lowest centroid value is the non-rewarded cluster. The results of this process form clusters, which are used for advice and consideration to determine sales strategy, namely to reward customers who rank higher in the cluster

Improving Vehicle Detection in Challenging Datasets: YOLOv5s and Frozen Layers Analysis Ahmad Nanda Yuma Rafi; Mohamad Yusuf
International Journal of Informatics and Computation Vol. 5 No. 2 (2023): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v5i2.64

Small datasets and imbalanced classes often cause problems when it used as primary research material. In case of classification and object detection, some researchers proposed Transfer Learning (TF) with several frozen layers. Moreover, YOLO (You Only Look Once) is one of the algorithms that works in real-time object detection. In this research, we focused on evaluating the YOLOv5s version of detecting vehicles in small and imbalanced datasets. The original YOLOv5s were trained and compared with YOLOv5s with freezing layers method (10 and 24 frozen layers). The experimental results of original YOLOv5s were precision score of 0.779, recall value of 0.933, mAP@0.5 of 0.93 and mAP@0.5:0.95 of 0.684 while YOLOv5s with 10 frozen layers where precision score was decreased to 0.639, but the other value increase with recall value of 0.939, mAP@0.5 of 0.951 and mAP@0.5:0.95 of 0.732. Overall, the version with 10 frozen layers demonstrated superior performance in addressing the challenges of small and imbalanced datasets, particularly excelling in recall and mAP metrics.

Line Crossing Detector System for Real-Time Over-Taking Vehicle Detection Ahmad Nanda Yuma Rafi; Mohamad Yusuf
International Journal of Informatics and Computation Vol. 6 No. 1 (2024): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v6i1.72

This study introduces a novel method for detecting overtaking vehicles by integrating Virtual Line Detection with the YOLOv8n algorithm. The objective is to enhance road safety by accurately identifying and tracking vehicles as they overtake, which is crucial for preventing. The research demonstrates the effectiveness of this approach, achieving a detection accuracy rate of 80.95% using line crossing detection techniques. This high level of accuracy underscores the potential of the system to reliably identify overtaking maneuvers in traffic conditions. Furthermore, this innovative method holds promising implications for enhancing safety riding by providing realtime alerts to drivers and preventing infrastructure loss resulting from traffic incidents. Our findings suggest that integrating advanced detection algorithms like YOLOv8n with virtual line detection can be a viable solution for modern traffic safety challenges.

Pembelajaran Dasar Keamanan Pengguna Sosial Media Pada Tim PKK Petugas Kelurahan Duri Kepa Kebon Jeruk Jakarta Barat Roy Mubarak; Mohamad Yusuf
Jurnal Abdimas Indonesia Vol. 4 No. 2 (2024): April-Juni 2024
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53769/jai.v4i2.704

Media sosial adalah platform digital yang memungkinkan pengguna untuk berinteraksi, berbagi konten, dan terhubung dengan orang lain secara online. Ini adalah sarana komunikasi yang sangat populer di seluruh dunia, memungkinkan individu, kelompok, dan organisasi untuk berbagi informasi, pandangan, dan pengalaman. Contoh dari platform media sosial adalah: Facebook, Instagram, Twitter LinkedIn, YouTube, Snapchat, TikTok, WhatsApp, Reddit dan Pinterest. Platform-platform ini menawarkan berbagai fitur dan pengalaman, dan masing-masing memiliki komunitas pengguna yang unik. Namun, penting untuk diingat bahwa penggunaan media sosial juga membawa risiko terkait privasi, keamanan, dan kesehatan mental, sehingga penting untuk menggunakan platform-platform tersebut dengan bijak. Contoh dari ancaman keamanan dari penggunaan sosial media adalah: Privasi dan Keamanan, Cyberbullying, Penyebaran Informasi Palsu (Hoaks), Pencurian identitas, Penipuan Online, Pemerasan Online dan lainnya. Sehingga keamanan dalam penggunaan media sosial adalah suatu hal yang sangat penting, mengingat risiko yang terkait dengan privasi, keamanan, dan kesehatan mental. Sehingga kegiatan pengabdian ini memang dirasakan banyak manfaatnya bagi masyarakat, salah satunya adalah upaya pencegahan dini dari upaya kejahatan dunia maya khususnya yang bersumber dari dampak penggunaan sosial media serta bagaimana cara bersosial media dengan bijak. Kebutuhan akan pemaparan dan pelatihan ini direalisasikan melalui kegiatan Pengabdian kepada Masyarakat (PkM) yang dilakukan oleh dosen dan mahasiswa sebagai salah satu Tridharma Perguruan Tinggi.

Penerapan Bahasa Pemrograman HTML Python sebagai perangkat pendukung dalam pelayanan Masyarakat Pada Tim PKK Kelurahan Duri Kepa Kebon Jeruk Jakarta Barat Mohamad Yusuf; Roy Mubarak; Rushendra Rushendra; Siti Maesaroh; Nungky Awang Candra
Jurnal Abdimas Indonesia Vol. 5 No. 1 (2025): Januari-Maret 2025
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34697/jai.v5i1.1327

Tim Pemberdayaan dan Kesejahteraan Keluarga (PKK) di Kecamatan Duri Kepa berperan penting dalam menyebarkan informasi dan mendukung pengambilan keputusan tentang kesehatan masyarakat. Dengan meningkatnya kebutuhan akan solusi berbasis web, pengetahuan tentang teknologi seperti HTML, CSS, dan Python menjadi semakin krusial. Teknologi ini memungkinkan pengembangan sistem informasi yang lebih interaktif dan efektif, bahkan untuk pemula. Untuk menghadapi tantangan ini, program pelatihan telah disiapkan untuk memberikan anggota PKK keterampilan yang diperlukan dalam pengembangan web. Pelatihan ini menerapkan metode pembelajaran interaktif dan langsung di laboratorium universitas, dengan penekanan pada praktik HTML dan Python. Metode ini memberikan kesempatan bagi peserta untuk menerapkan keterampilan yang diperoleh dalam proyek berbasis web yang relevan dengan tugas mereka di PKK. Hasil dari kegiatan ini menunjukkan bahwa pelatihan berlangsung sukses dan peserta menunjukkan antusiasme yang tinggi. Mereka merasa nyaman dalam mengikuti pelatihan dan mampu menggunakan pengetahuan tentang HTML dan Python untuk membuat aplikasi sederhana. Program ini diharapkan dapat meningkatkan efektivitas intervensi kesehatan di tingkat komunitas serta mendukung pengambilan keputusan yang berbasis data dan berkelanjutan dalam konteks kesehatan masyarakat.

SOSIALISASI PENGENALAN APLIKASI STUNTING DAN TUMBUH KEMBANG BALITA PADA DESA CIPUTRI –KABUPATEN CIANJUR Hakim, Lukman; Santoso, Hadi; Yusuf, Mohamad
Jurnal Pengabdian dan Kewirausahaan Vol 9, No 1 (2025): Jurnal Pengabdian dan Kewirausahaan
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/jpk.v9i1.8190

Government Policies on Improving Nutritious Eating as a Priority in Combating Stunting The government’s policy to enhance nutritious eating is currently a priority in addressing stunting, as outlined in Presidential Regulation No. 72 of 2021 on Stunting Reduction. Stunting is a growth impairment condition caused by recurrent malnutrition. Ciputri Village, located in Pacet District, Cianjur Regency, with an area of 6.36 hectares and comprising four hamlets, still has a stunting prevalence of 1.03% among toddlers. A community service program involving LLDIKTI 3, in collaboration with the Cianjur Regency and several universities in Jakarta, was conducted. The purpose of the program was to provide understanding and socialization on the impacts and factors contributing to stunting in toddlers, as well as the use of a stunting application for monitoring the growth and development history of toddlers. The community service activities included preparatory observations and implementation on November 13-14, 2024. The program involved the presentation of the stunting and growth monitoring application and explanations of facial recognition for accessing the application. The program was attended by 25 participants, and the results were evaluated through a questionnaire. Based on the questionnaire, the expectation score was 3.52, while the reality score was 3.48 on a scale of 1-4, indicating overall satisfaction with the community service program.

Implementasi Chatbot Cuaca Berbasis SBERT dan LLM Gemini Menggunakan OpenWeather API Hanif luthfi Irfanudin; Mohamad Yusuf
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 7 No. 1 (2026): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v7i1.1770

This study discusses the development of a Natural Language Processing (NLP)-based weather chatbot dashboard capable of receiving natural Indonesian language queries and displaying weather information interactively. The system combines Sentence-BERT (SBERT) paraphrase-multilingual-MiniLM-L12-v2 as a text similarity engine, Gemini 2.5-flash Large Language Model (LLM) as a natural language summary generator, and the OpenWeather API as a real-time weather data source. A zero-shot semantic similarity approach is used without fine-tuning, with intent determination based on cosine similarity and a threshold of 0.5 optimized through testing several threshold values. The development method used is the Waterfall model with stages of requirements analysis, architectural design, NLP module implementation and API integration, React dashboard frontend development, as well as functional black-box testing and performance metric evaluation. The test results show that SBERT with a threshold of 0.5 produces an intent classification accuracy of 90% in 20 test scenarios, which increases to 100% after being combined with rule-based auto-adjust and fallback mechanisms. City entity extraction with a 1–3 word sliding window against city.list.json achieved 100% accuracy on 15 city-based queries, while macro metrics yielded a precision of 0.9286, a recall of 0.90, and an F1‑score of 0.8958. The integration of the OpenWeather API and Gemini enables the presentation of natural, informative weather summaries and visualization of real-time weather data in the form of interactive graphs on a React-based dashboard.

Construction and Management of a Cosmos-Based Operating System Using Visual Studio Development and VMware Virtualization Technology Mohamad Yusuf; Zidane Fahrezi; Rafif Syari Hidayah; Yudha Andika Istanto; Gilas Adi Saputra
Journal Collabits Vol. 1 No. 1 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i1.25559

Operating systems play an important role in bridging hardware and software on various computing devices. This research focuses on building an operating system based on Cosmos, an open source project that allows the creation of operating system kernels quickly and efficiently. In the process, we leverage Visual Studio development tools to develop and maintain the kernel, while VMware virtualization technology is used to test and manage development. This research contributes to further understanding of the development of Cosmos-based operating systems with optimal use of Visual Studio development tools and VMware virtualization technology

Optimisation of the Competency Assessment System Through Matrix Applications and Linear Algebra Using the AHP Method Nabil Ahmad Furqon; Ius Andre Virganata; Maulana Arvian Wibisana; Qalbiridha Albarra; Mohamad Yusuf
Journal Collabits Vol. 2 No. 2 (2025)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v2i2.32523

Competency-based assessment systems are increasingly important in education and industry to objectively assess individual abilities, overcoming the subjectivity issues inherent in traditional assessment methods. This study aims to develop an innovative competency assessment system by combining Assessment Matrix and Linear Algebra, specifically using the Analytic Hierarchy Process (AHP) method to systematically and accurately determine the weight of criteria. The research data were taken from a dataset of college students, with five main criteria of competence, including technical skills, cooperation, and creativity. The data normalization process was carried out using Min-Max Scaling and Z-Score Normalization to ensure consistency, followed by the construction of an AHP comparison matrix based on the level of importance between criteria. The weight of the criteria was calculated using the eigenvector method, and the consistency test was carried out through the Consistency Ratio (CR) to ensure the validity of the matrix (CR < 0.1). The final assessment was obtained by multiplying the AHP weights by the student's scores for each criterion. The results showed that this approach resulted in a more objective, transparent, and accurate assessment system than conventional methods, with the potential to improve fairness in evaluation in the academic environment. This research provides a new contribution in the application of linear algebra to the development of competency assessment systems, as well as offering practical solutions for educators and human resource managers in improving performance evaluation.

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